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PowerNap: eliminating server idle power

Published: 07 March 2009 Publication History

Abstract

Data center power consumption is growing to unprecedented levels: the EPA estimates U.S. data centers will consume 100 billion kilowatt hours annually by 2011. Much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still consume 60% of their peak power draw. Typical idle periods though frequent--last seconds or less, confounding simple energy-conservation approaches.
In this paper, we propose PowerNap, an energy-conservation approach where the entire system transitions rapidly between a high-performance active state and a near-zero-power idle state in response to instantaneous load. Rather than requiring fine-grained power-performance states and complex load-proportional operation from each system component, PowerNap instead calls for minimizing idle power and transition time, which are simpler optimization goals. Based on the PowerNap concept, we develop requirements and outline mechanisms to eliminate idle power waste in enterprise blade servers. Because PowerNap operates in low-efficiency regions of current blade center power supplies, we introduce the Redundant Array for Inexpensive Load Sharing (RAILS), a power provisioning approach that provides high conversion efficiency across the entire range of PowerNap's power demands. Using utilization traces collected from enterprise-scale commercial deployments, we demonstrate that, together, PowerNap and RAILS reduce average server power consumption by 74%.

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Information & Contributors

Information

Published In

cover image ACM SIGARCH Computer Architecture News
ACM SIGARCH Computer Architecture News  Volume 37, Issue 1
ASPLOS 2009
March 2009
346 pages
ISSN:0163-5964
DOI:10.1145/2528521
Issue’s Table of Contents
  • cover image ACM Conferences
    ASPLOS XIV: Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
    March 2009
    358 pages
    ISBN:9781605584065
    DOI:10.1145/1508244
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2009
Published in SIGARCH Volume 37, Issue 1

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  1. power management
  2. servers

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Cited By

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  • (2025)Multimodal information fusion and artificial intelligence approaches for sustainable computing in data centersPattern Recognition Letters10.1016/j.patrec.2024.12.006189(17-22)Online publication date: Mar-2025
  • (2024)Data Center Sustainability: Revisits and OutlooksIEEE Transactions on Sustainable Computing10.1109/TSUSC.2023.32815839:3(236-248)Online publication date: May-2024
  • (2024)Intelligent Decision-Based Edge Server Sleep for Green Computing in MEC-Enabled IoV NetworksIEEE Transactions on Intelligent Vehicles10.1109/TIV.2023.33478339:2(3687-3703)Online publication date: Feb-2024
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  • (2024)Data Center Power and Energy Management: Past, Present, and FutureIEEE Micro10.1109/MM.2024.342647844:5(30-36)Online publication date: 1-Sep-2024
  • (2024)Heterogeneous Hyperthreading2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00018(68-78)Online publication date: 27-May-2024
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